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- Energy Consumption Management in Buildings in the Context of Voluntary and Mandatory Demand Response Programs in Smart GridsPublication . Khorram Ghahfarrokhi, Mahsa; Zheiry, Modar; Faria, Pedro; Vale, ZitaEnergy consumption is increasing around the world and has been made many consequences such as increasing greenhouse emissions, global warming, and climate changes. Demand response programs can be considered as techniques to manage and control electricity consumption based on user flexibility. There are several types of demand response programs that are categorized in price-based programs and incentive-based programs. This paper analyzes real demand response implementations according to a dataset provided by the Federal Energy Regulatory Commission. Real demand response programs are analyzed based on customer type, program type, potential and capability of the programs, and controllable loads. In the case study, an optimization approach is proposed to control the loads and achieve the power reduction goals of the demand response programs. The obtained results show how buildings can be participants in demand response programs, choosing the more advantageous program.
- Air Conditioning Consumption Optimization Based on CO2 Concentration LevelPublication . Khorram Ghahfarrokhi, Mahsa; Zheiry, Modar; Faria, Pedro; Vale, ZitaNowadays, energy consumption increasing is a big concern for many countries around the world. Disadvantages and consequences of fossil fuels for the environment caused a lot of efforts to invest in renewable energy resources and programs to optimize energy consumption. All types of buildings are the major consumers of electric power. Therefore, buildings can be considered as good options for implementing optimization algorithms, assuming that they are equipped to required infrastructures. Air conditioners are flexible loads that can be directly controlled by optimization programs. This paper presents a particle swarm optimization algorithm to minimize the power consumption of the air conditioners based on the carbon dioxide concentration level. The algorithm considers the thermal comfort of users with defining restrictions. The case study of the paper proposes two scenarios with real monitored data of a building. The result of the paper shows the obtained results of the algorithm and makes the comparison of two scenarios.
- Economic Impact of an Optimization-Based SCADA Model for an Office BuildingPublication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Abrishambaf, Omid; Vale, ZitaThe daily increment of electricity usage has led many efforts on the network operators to reduce the consumption in the demand side. The use of renewable energy resources in smart grid concepts became an irrefutable fact around the world. Therefore, real case studies should be developed to validate the business models performance before the massive production. This paper surveys the economic impact of an optimization-based Supervisory Control And Data Acquisition model for an office building by taking advantages of renewable resources for optimally managing the energy consumption. An optimization algorithm is developed for this model to minimize the electricity bill of the building considering day-ahead hourly market prices. In the case study, the proposed system is employed for demonstrating electricity cost reduction by using optimization capabilities based on user preferences and comfort level. The results proved by the performance of the system, which leads to having great economic benefits in the annual electricity cost.
- CO2 Concentration Forecasting in an Office Using Artificial Neural NetworkPublication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Abrishambaf, Omid; Vale, Zita; Soares, JoãoUncertainty is the state of all operation, components, and objective environment that makes impossible to describe the existing state. Forecasting techniques are essential in the field of knowledge development to overcome the uncertainty to increase the efficiency of all systems. In this paper, artificial neural network algorithm is applied to forecast the CO2 concentration in an office building. The algorithm is implemented in Rstudio software using neural net package. The case study of the paper presents two scenarios with different input data to propose the impacts of train data on forecasting algorithms results. The used dataset in the case study is real data that have been monitored for 2 years. The obtained results of algorithms show the predicted values of CO2 concentration in one office for 600 minutes of a working day. The mean percentage error means absolute percentage error, and standard deviation of predicted data for both scenarios are presented in results section.
- Lighting Consumption Optimization in an Office Building for Demand Response ParticipationPublication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Abrishambaf, Omid; Vale, ZitaDue to daily increment of electricity demand all around the world, the use of renewable energy resources and the methods of energy optimization are being important. Since the lighting systems have a pivotal role in the energy consumption of the buildings, the optimization of the lighting system should be effective. Hence, the focus of this paper is to minimize the lights consumption of an office building, while participating in demand response programs. The methodology of this work is proposed as a linear optimization problem that manages the generation of a renewable energy resource, which supplies a part of the energy consumption of the building. The lighting system of the building consists of the several laboratorial and commercial equipment, utilizing different communication interfaces. For the case studies, the amount of the renewable energy generation, total consumption of building, and the consumption of the lights in a real research building are considered.
- Sequential Tasks Shifting for Participation in Demand Response ProgramsPublication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Vale, Zita; Ramos, CarlosIn this paper, the proposed methodology minimizes the electricity cost of a laundry room by means of load shifting. The laundry room is equipped with washing machines, dryers, and irons. Additionally, the optimization model handles demand response signals, respecting user preferences while providing the required demand reduction. The sequence of devices operation is also modeled, ensuring correct operation cycles of different types of devices which are not allowed to overlap or have sequence rules. The implemented demand response program specifies a power consumption limit in each period and offers discounts for energy prices as incentives. In addition, users can define the required number of operations for each device in specific periods, and the preferences regarding the operation of consecutive days. In the case study, results have been obtained regarding six scenarios that have been defined to survey about effects of different energy tariffs, power limitations, and incentives, in a laundry room equipped with three washing machines, two dryers, and one iron. A sensitivity analysis of the power consumption limit is presented. The results show that the proposed methodology is able to accommodate the implemented scenario, respecting user preferences and demand response program, minimizing energy costs. The final electricity price has been calculated for all scenarios to discuss the more effective schedule in each scenario.
- Air conditioner consumption optimization in an office building considering user comfortPublication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Abrishambaf, Omid; Vale, ZitaThe rapid growth of energy consumption and its consequences in the last decades, made the world persuaded to energy optimization and energy management. Therefore, producers and prosumers should be equipped with the automation infrastructures to perform the management programs, such as demand response programs. Office buildings are considering as a proper case for implementing energy consumption minimization since they are responsible for a huge portion of total energy consumption in the world. This paper proposes a multi-period optimization algorithm implemented in Supervisory Control and Data Acquisition system of an office building. The developed optimization algorithm is an efficient solution considered for minimizing the power consumption of air conditioners by considering the user comfort constraints. Two determinative parameters are defined to prevent over-power reduction from certain devices. In order to respect to user preferences, priority numbers are dedicated to each air conditioner to present the importance of each device. A case study with several scenarios is implemented to verify the performance of the proposed algorithm in real life using real data of the building. The obtained results show the impacts of proposed parameters and different comfort constraints of algorithm while the main target of the optimization has been reached.
- Demand Response Implementation in an Optimization Based SCADA Model Under Real-Time Pricing SchemesPublication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Abrishambaf, Omid; Vale, ZitaAdvancement of renewable energy resources, development of smart grids, and the effectiveness of demand response programs, can be considered as solutions to deal with the rising of energy consumption. However, there is no benefit if the consumers do not have enough automation infrastructure to use the facilities. Since the entire kinds of buildings have a massive portion in electricity usage, equipping them with optimization-based systems can be very effective. For this purpose, this paper proposes an optimization-based model implemented in a Supervisory Control and Data Acquisition, and Multi Agent System. This optimization model is based on power reduction of air conditioners and lighting systems of an office building with respect to the price-based demand response programs, such as real-time pricing. The proposed system utilizes several agents associated with the different distributed based controller devices in order to perform decision making locally and communicate with other agents to fulfill the overall system’s goal. In the case study of the paper, the proposed system is used in order to show the cost reduction in the energy bill of the building, while it respects the user preferences and comfort level.
- D7.3 Proceedings of the Second DREAM-GO Workshop: Real-Time Demand Response and Intelligent Direct Load ControlPublication . Vale, Zita; Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Spínola, João; Canizes, Bruno; Pinto, Tiago; Soares, João; Chamoso, Pablo; Santos, Daniel; Garcia, Oscar; Catalina, Jorge; Guevarra, Fabio; Navarro-Cáceres, María; Gazafroudi, Amin Shokri; Prieto-Castrillo, Francisco; Corchado, Juan Manuel; Santos, Gabriel; Teixeira, Brígida; Praça, Isabel; Sousa, Filipe; Zawislak, Krzysztof; Iglesia, Daniel Hernández de la; Barriuso, Alberto Lopez; Lozano, Alvaro; Herrero, Jorge Revuelta; Landeck, Jorge; Paz, Juan F. de; Corchado, Juan M.; Garcia, Ruben Martin; González, Gabriel Villarrubia; Bajo, Javier; Matos, Luisa; Klein, L. Pires; Carreira, R.; Torres, I.; Landeck, JorgeProceedings of the Second DREAM-GO Workshop Real-Time Demand Response and Intelligent Direct Load Control
- Lighting Consumption Optimization in a SCADA Model of Office Building Considering User Comfort LevelPublication . Khorram Ghahfarrokhi, Mahsa; Faria, Pedro; Vale, ZitaDue to the high penetration of the buildings in energy consumption, the use of optimization algorithms plays a key role. Therefore, all the producers and prosumers should be equipped with the automation infrastructures as well as intelligent decision algorithms, in order to perform the management programs, like demand response. This paper proposes a multi-period optimization algorithm implemented in a multi-agent Supervisory Control and Data Acquisition system of an office building. The algorithm optimizes the lighting power consumption of the building considering the user comfort constraints. A case study is implemented in order to validate and survey the performance of the implemented optimization algorithm using real consumption data of the building. The outcomes of the case study show the great impact of the user comfort constraints in the optimization level by respect to the office user’s preferences.